Cross-channel correlation of consumer telephone numbers and user identifiers

ABSTRACT

A method and system that performs cross-channel correlation of user identifiers with consumer telephone numbers. The system receives impression data characterizing the exposure of users to mechanisms for contacting businesses, the impression data including associated phone number and a date and time for each of the exposures. The system also receives call data describing telephone calls to businesses, the call data including a caller telephone number, a callee telephone number, and a date and time for each of the calls. Based on matching impression telephone numbers and call data callee numbers, the system forms correlations between corresponding user identifiers and caller telephone numbers. Correlations are also assigned a confidence level, based on the date and time of the corresponding exposures and telephone calls, that reflects the likelihood that a user associated with the correlated user identifier is the same as the user associated with the correlated caller telephone number.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application is a continuation of U.S. patent application Ser. No.13/865,966, entitled “CORRELATED CONSUMER TELEPHONE NUMBERS AND USERIDENTIFIERS FOR ADVERTISING RETARGETING,” filed Apr. 18, 2013, whichclaims the benefit of U.S. Provisional Patent Application No.61/801,893, entitled “CROSS-CHANNEL TARGETING USING HISTORICAL ONLINEAND CALL DATA,” filed Mar. 15, 2013, all of which are incorporatedherein by reference in their entireties.

BACKGROUND

Businesses nowadays interact with customers and prospective customersusing a variety of communication channels, such as via wired or wirelesstelephone networks, the Internet, interactive television systems, andin-person at brick-and-mortar stores. Although each communicationchannel can be somewhat successful by itself in reaching any particularcustomer, there exists information inefficiencies when a customerinteracts with the businesses across more than one of the communicationchannels. For example, if a potential customer is using a telephonesystem to enquire about the products or services of a business, but doesnot complete a transaction, the business is rarely able to re-engagewith the customer. Although the business would like to target thepotential customer with advertising in the hopes of completing a sale,there is no convenient mechanism to do so. The business may call thepotential customer back, but such an approach is considered intrusiveand off-putting by many customers. At best, the business must hope thatthe customer randomly stumbles across advertising associated with thebusiness, or is sufficiently motivated to call or visit the businessagain in the future. The ability to leverage the fact that the consumerused a phone to contact the business is typically lost.

Thus, there is a need for a system and method that can take intoconsideration a consumer's engagement with a business via the phone andapply that information when determining which users to target for amarketing campaign conducted across a second communication channel, suchas via online advertising.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a system for cross-channel advertising inaccordance with the disclosed technology, the system utilizing across-channel targeting database to allow consumers to be re-targetedbased on their phone number.

FIGS. 2A and 2B are exemplary data structures of identity, interaction,and/or activity data provided by publishers to the cross-channeladvertising system.

FIG. 3 is an exemplary data structure of interaction data provided bybusinesses to the cross-channel advertising system.

FIG. 4 is an exemplary data structure maintained in a cross-channeltargeting database by the cross-channel advertising system.

FIG. 5 is a flow diagram illustrating a process implemented by thecross-channel advertising system for performing cross-channel targetingof advertisements.

DETAILED DESCRIPTION

A method and system that performs cross-channel advertisement targetingusing historical online and call data is disclosed herein. The systemutilizes a cross-channel targeting database to identify consumers thatshould be reengaged (or, “re-targeted”) on behalf of a business via analternate communication channel. The cross-channel targeting databasecorrelates masked user identifiers representing online activities ofconsumers with telephone numbers associated with each consumer. A maskeduser identifier is provided by a website publisher or other party and isassociated with a unique identifier that is used by the publisher orother party to track the online behavior of a consumer (e.g., a cookie,a device or subscriber identifier, a user ID). The correlation betweenunique user identifier (and hence masked identifier) and telephonenumber may be explicitly identified, such as when a consumer provides aphone number to a website as part of a log-in process or as part of apurchase of a good or service through the website. The correlationbetween unique user identifier (and hence masked identifier) andtelephone number may also be implicitly identified, such as when atracking telephone number is displayed in an advertisement on aconsumer's computing device and a call is received to that trackingtelephone number within a threshold period after display of theadvertisement. Because of the inherent uncertainty in drawingcorrelations between unique user identifiers (and therefore masked useridentifiers) and telephone numbers, the cross-channel targeting databasemay include a confidence level associated with the correlated valuetuples (masked user ID, publisher ID, telephone number). The confidencelevel represents the likelihood that a particular telephone number iscorrelated with a particular masked user identifier for the identifiedpublisher.

The cross-channel targeting database is used by the system to targetadvertisements to consumers. Businesses continually receive telephonecalls from potential customers that do not result in a potential sale.For example, callers may call a business to ask questions about aproduct or seek details about a business (e.g., hours of operation,directions to the business). When a business receives calls from anindividual, they are often able to identify the caller from caller ID.In order to target advertisements to those customers that have failed toconvert as a result of the telephone call, businesses may provide thecaller's telephone number and a desired advertisement or advertisingcampaign to the system. Using the cross-targeting database, the systemidentifies the masked user identifier or identifiers that is associatedwith the telephone number and the publisher or publishers that generatedthe masked user identifier or identifiers. The system uses theidentified masked user identifiers and publishers to target theadvertisement or advertising campaign to the consumer. The systemthereby allows contacts to a business that are received on one channel(e.g., the telephone) to be re-engaged by targeted advertising in asecond channel (e.g., via a browser application that receivesadvertisements over a network).

In some embodiments, the stored confidence level representing thelikelihood of correspondence between a telephone number and a maskeduser identifier is used by the system to control the aggressiveness ofre-targeting. A business may set a confidence threshold that they wouldlike to have exceeded before re-targeting occurs. The confidencethreshold value is specified by the business in order to control howbroadly or narrowly the re-targeting campaign is to be focused. Thesystem may also utilize various other re-targeting conditions and/ortechniques to increase the accuracy and effectiveness of there-targeting campaign. These additional criteria and techniques will bedescribed in detail below.

Various embodiments of the invention will now be described with specificreference to the Drawings. The following description provides specificdetails for a thorough understanding and an enabling description ofthese embodiments. One skilled in the art will understand, however, thatthe invention may be practiced without many of these details.Additionally, some well-known structures or functions may not be shownor described in detail, so as to avoid unnecessarily obscuring therelevant description of the various embodiments. The terminology used inthe description presented below is intended to be interpreted in itsbroadest reasonable manner, even though it is being used in conjunctionwith a detailed description of certain specific embodiments of theinvention.

FIG. 1 is a block diagram illustrating a representative environment 100in which a cross-channel advertising system 102 may operate. The system102 utilizes a cross-channel targeting database 104 that correlates atelephone number of a consumer with a masked user identifier associatedwith that consumer. The correlation between telephone number and maskeduser identifier is used by the system to target advertisements to theconsumer across a different channel than an original contact with theconsumer occurred. The system 102 operates on one or more computingdevices, such as server computers which may be configured in whole or inpart as a web service. The system 102 utilizes one or more processors106 (“CPU”) to execute instructions that perform various actions andimplement decision logic. The computer executable instructions arestored in volatile or non-volatile memory 108 along with other data.

Those skilled in the art will appreciate that the system 102 may beimplemented on any computing system or device. Suitable computingsystems or devices include personal computers, server computers,multiprocessor systems, microprocessor-based systems, network devices,minicomputers, mainframe computers, distributed computing environmentsthat include any of the foregoing, and the like. Such computing systemsor devices may include one or more processors that execute software toperform the functions described herein. Processors include programmablegeneral-purpose or special-purpose microprocessors, programmablecontrollers, application specific integrated circuits (ASICs),programmable logic devices (PLDs), or the like, or a combination of suchdevices. Software may be stored in memory, such as random access memory(RAM), read-only memory (ROM), flash memory, or the like, or acombination of such components. Software may also be stored in one ormore storage devices, such as magnetic or optical based disks, flashmemory devices, or any other type of non-volatile storage medium forstoring data. Software may include one or more program modules whichinclude routines, programs, objects, components, data structures, and soon that perform particular tasks or implement particular abstract datatypes. The functionality of the program modules may be combined ordistributed across multiple computing systems or devices as desired invarious embodiments.

The system 102 receives data associated with two types of interactionsinvolving consumers 110. The first type of interaction is betweenconsumers 110 and publishers 112 over a data channel 114. A record ofthe identity and/or interactions between the consumers and publishersover the data channel is used to populate the cross-channel targetingdatabase 104. The second type of interaction is between consumers 110and businesses 116 over a voice channel 118. A record of the identityand/or interactions between consumers and businesses over the voicechannel may be used to populate the cross-channel database, but may alsoused by the system to identify potential customers on which to performtargeting advertising on behalf of a business. Each type of interactionwill be described in turn.

In the first type of interaction, a consumer 110 a uses a computingdevice 120 having a web browser or other application to interact with apublisher website 112 a (e.g., Google, Yahoo!, New York Times, Facebook)or a publisher application 112 n (e.g., an application installed on amobile device). The computing device may be a personal computer, laptopcomputer, notebook computer, tablet computer, smartphone, portable mediaplayer, gaming device, or other computing device that allows a consumerto access websites or applications. The computing device 120 relies upona network 122 such as the Internet to connect to publisher websites orapplications. Network 122 may be any private or public, wired orwireless, network. The publisher website 112 a is hosted on one or moreweb servers that serve content to the consumer. The consumer's computingdevice 120 fetches, displays, and interacts with the web server via HTTPor other supported communication protocol. To allow the consumer'sonline activity to be tracked, a publisher may use a unique useridentifier 124 to track activities of the consumer each time an Internetdomain accessed. The unique user identifier 124 may be a cookieassociated with a browser, a unique device identifier such as anInternational Mobile Station Equipment Identity (IMEI) number, anInternational Mobile Subscriber Identifier (IMSI), or other identifierthat may be placed on the computing device or read by the publisher. Forexample, if a consumer 110 a visits a website, the publisher serving thedomain may place a cookie on the consumer's computer or mobile devicereflecting the website session and certain activities what wereperformed during the session. The publisher 112 maintains a record ofthe consumer's interaction with the website or application, including arecord of any advertisements that were served by the publisher to theconsumer's computing device. If the consumer 110 returns to apublisher's website, additional website actions and advertisements maybe associated with the consumer by virtue of the stored cookie or otherunique user identifier.

As part of the consumer's interaction with the publisher website and/orapplication, the publisher 112 may receive sufficient information toidentify a telephone number 128 associated with the consumer, andcorrelate the identified telephone number 128 with the unique useridentifier 124. For example, if the consumer is required to establish anaccount with the publisher 112 in order to access certain features ofthe publisher's website, during the account set-up process the consumermay be required to provide a telephone number at which the consumer canbe reached. When the consumer subsequently returns to the publisherwebsite and logs-in to the consumer's account to access the websitefeatures, the publisher 112 is thereby able to associate the onlineactivities of the consumer, including any advertisements presented tothe consumer, with the consumer's telephone number.

As another example of how a publisher 112 may receive sufficientinformation to correlate a telephone number 128 to the unique useridentifier 124, the consumer may provide a telephone number as part of atransaction with a publisher website. For example, the consumer mayorder goods and services from the website by filling out a transactionform and including a name, address, phone number, payment information,and other details. If the consumer 110 expressly provides a phone numberas part of a transaction with the website, the publisher 112 is therebyable to correlate the online activities of the consumer, including anyadvertisements presented to the consumer, with the consumer's telephonenumber.

On a continuous or periodic basis, publishers 112 may provide thecross-channel advertising system 102 with identity, impression, and/oractivity data that the publishers compile as a result of monitoringconsumer interaction with websites 112 a or applications 112 n. Becausepublishers may be reticent to share the actual unique user identifier124, in some embodiments a publisher may apply a masking algorithm tothe user identifier. That is, the publisher may apply a hash or othermathematical operation to the user identifier to mask the actualidentifier from the cross-channel advertising system. Alternatively, thepublisher may construct a table or other technique that maps the uniqueuser identifier 124 to a generated masked user identifier. The publisherprovides the masked user identifier to the cross-channel advertisingsystem 102 rather than the actual user identifier 124. The purpose ofthe masked user identifier is to hide the actual value of the useridentifier 124 from the cross-channel advertising system 102, yet stillallow the publisher to correlate a received masked user identifier witha user identifier 124 in order to target a consumer with a desiredadvertisement. In some embodiments, instead of providing a masked useridentifier the publisher provides the actual value of the useridentifier 124 to the cross-channel advertising system 102. The actualvalue may be the cookie, IMEI, IMSI, media access control address (MACaddress), hardware/software fingerprint, etc., of the consumer'scomputing device. In circumstances where the actual value of the useridentifier 124 is provided by a publisher, the system 102 may be able toidentify the same consumer across different publishers based on theprovided user identifier. Although the figures and description primarilyrefer to masked user identifiers, it will be appreciated that thedescribed techniques are similarly applicable to embodiments in whichthe actual value of the user user identifier 124 is provided by apublisher.

The identity, impression, and/or activity data may be transmitted by apublisher to the cross-channel advertising system 102 via an API,delivered via FTP, provided via storage media such as optical disk, etc.It will be appreciated that the cross-channel advertising system 102 maybe operated by a third-party that is distinct from the publishers, or itmay be operated by a publisher itself.

FIG. 2A is an example of a representative data table 200 containingmasked user identifiers that are provided by a publisher 112 to thesystem 102. A publisher identifier (not shown) is associated with thetable and used to identify the corresponding publisher from which thedata is received. The data in the table 200 is used by the system tobuild a profile of consumers for purposes of identifying re-targetingopportunities. Each row in the table 200 represents identity informationthat is generated as a result of a prior interaction of a consumer withthe publisher via data channel 114. Each column in the table 200represents different data fields that characterize the consumer. Thefirst field is a reference number field 210 that contains a uniqueidentifier that is assigned by the publisher 112 to the record. Thereference number may be assigned by the publisher to facilitate datasynching with the cross-channel advertising system 102. The second fieldis a masked user identifier field 210 that is populated with a maskeduser identifier provided by the publisher. A mapping is maintained bythe publisher of each masked user identifier and a unique identifierassociated with the consumer or the consumer's device. For example, themasked identifier may be mapped by the publisher to a cookie that isassociated with the consumer's browser at the time of the interaction.As another example, the masked identifier may be mapped by the publisherto the IMEI of the computing device that the consumer used at the timeof the interaction. It will be appreciated that other unique identifiersincluding, but not limited to, a media access control address (MACaddress) or hardware/software fingerprint may also be used by apublisher to identify the computing device used by the consumer. In thedepicted example, row 202 includes the masked user identifier (e.g.,“5843DC484”) provided by the publisher. A time and date field 216 may bepopulated by the system with a time and date stamp of when each recordwas received from the publisher. In the depicted example, the identityinformation was received from the publisher at 8:42 am on Dec. 12, 2012.As will be described in additional detail herein, the contents of thetime and date field 216 may be used by the system to assess thelikelihood that the associated identity data is still accurate.

It will be appreciated that while the information contained in table 200is characterized as being received from a single publisher, the system102 will typically receive information from multiple publishers. Inthose circumstances, the system may maintain multiple tables 200, eachof which is associated with a corresponding publisher so that the systemcan track the source of the underlying data. Alternatively, each entryin a table 200 may have an assigned publisher ID so that the system canassociate each entry in the table with the corresponding publisher fromwhich it was received.

FIG. 2A depicts a minimal amount of information (masked user ID/userphone number) that may be received by the system 102 and used toconstruct the cross-channel targeting database 104. In contrast, FIG. 2Bis an example of a more robust data table 250 that contains impressionand activity data in addition to the identity information provided by asingle publisher 112. The data in table 250 may be provided bypublishers that are more willing to share impression or activity datawith the system 102 in anticipation of receiving better advertisingtargeting.

The data in the table 250 is used by the system to build a profile ofconsumers for purposes of identifying re-targeting opportunities. Eachrow in the table 250 is a record of an interaction of a consumer with apublisher 112 via the data channel 114. Each column in the table 200represents different data fields that characterize the interaction. Forexample, row 260 of the table corresponds to an advertisement that wasdelivered to a consumer by a publisher. The first four fields in table250 serve the same purpose as the corresponding fields in table 200.That is, the reference number field 210 contains a unique identifierthat is assigned by the publisher 112 to the interaction record. Themasked user identifier field 210 contains a masked user identifierprovided by the publisher. The time and date field 216 may be populatedwith a time and date stamp of when the consumer interaction occurred. Inthe depicted example, the consumer was presented with an advertisementat 8:42 am on Jul. 7, 2012.

In addition to the reference number and masked user identifier beingprovided by the publisher 112, additional pertinent informationsurrounding the consumer's interaction with the website or applicationmay be provided by the publisher. The table 250 also contains anadvertisement field 252 that may be populated with an indication of theone or more ads that were shown to the consumer during the interaction.In the depicted example, row 260 indicates that an advertisement wasshown to the consumer, and that the presented advertisement included thetracking telephone number 1-800-{TRACKING #}. As will be described inadditional detail herein, the number displayed in the advertisement maybe used by the system to later identify the consumer that called thenumber. One skilled in the art will appreciate that although the phonenumber of the advertisement is shown in the table for convenience, thesystem may be able to identify the phone number by other means. Forexample, the cross-channel advertising system may be able to identifythe phone number by analyzing the advertisement identified by the adtreatment number (e.g., #145343) in the ad field 252. Alternatively, thecross-channel advertising system 102 may have provided one or moretracking telephone numbers to the corresponding publisher for use in theads, and the system therefore have previous knowledge of what telephonenumbers would be contained in displayed advertisements.

The consumer interaction reflected in row 262 of the table 250 wasassociated with the display of an advertisement to the consumer. Incontrast, the consumer interaction in row 264 represents a purchase ofan item from the website by the consumer. The interaction represented byrow 264 contains much of the same data characterizing the interaction asrow 262, namely a reference number in field 210, a unique useridentifier in field 212, and the time and date of the interaction infield 216. In addition, however, the interaction in row 264 is alsocharacterized by information associated with the purchase. A user phonenumber field 214 contains a phone number (e.g., “206-255-1212”) that theconsumer provided to the publisher as part of the transaction. The phonenumber may be provided by the consumer at the time of purchase, or maybe stored in an account that the user maintains with the publisher andaccessed by providing log-in information to the publisher at the time ofthe transaction. A transactions field 254 contains a characterization ofthe consumer's transaction with the publisher. In the depicted example,the consumer is characterized as having “purchased Adidas soccer ball.”It will be appreciated that a greater or lesser amount of informationcharacterizing the purchase may be included in the transactions field,including a price, quantity, shipping information, etc. In addition, an“other” field 256 may be populated by the publisher 212 with anyadditional information that the publisher is willing to provide aboutthe consumer's interaction with the publisher.

A third interaction is represented by the row 236 in the table 250. Therow 236 represents an interaction where the consumer was presented withan advertisement by the publisher 212. In addition to all of the detailssurrounding the presentation of the advertisement to the consumer, therow 236 also contains a phone number (e.g., “414-555-1212”) of the user.The phone number of the user may have been obtained by the publisher asa result of an account with the publisher that is maintained by theconsumer.

It will be appreciated that while the information contained in table 250is characterized as being received from a single publisher, the system102 will typically receive information from multiple publishers. Inthose circumstances, a publisher ID (not shown) may be associated withthe each received table 250 so that the system tracks the source of theunderlying data.

It will be appreciated by one skilled in the art that the amount ofinteraction data that is provided by a publisher to the cross-channeladvertising system 102 may vary from publisher-to-publisher. Somepublishers 212 may be willing to provide significant details associatedwith consumer transactions, as doing so may allow the cross-channeladvertising system 102 to better target advertisements to consumers thatvisit the publisher. Other publishers may be reticent to share muchinformation with the advertising system 102, so may limit or curtail theamount of data that they provide to the system. As previously discussed,in minimal circumstances a publisher may be willing to provide a maskeduser identifier and a user phone number of a consumer to facilitatetargeting of advertisements by the advertising system 102.

In addition to publishers 212 providing interaction data to thecross-channel advertising system 102, other parties may also have accessto similar information that would allow correlation between a uniqueuser identifier 124 associated with a consumer's computing device 120and telephone number of the consumer. For example, if the user'scomputing device 120 is a smartphone, a vertically-integrated smartphonemanufacturer (not shown) may have access to the telephone numberassociated with the device as well as a unique identifier (such as theIMEI) associated with the device. In addition, the smartphonemanufacturer may be able to track the consumer's activities acrosspublisher websites and applications. As such, the smartphonemanufacturer would be able to provide similar information 126 to thecross-channel advertising system 102 as is contained in table 200. Inparticular, the smartphone manufacturer would be able to provide themasked user identifier and the telephone number of the smartphone thatis used by the consumer.

The foregoing describes many of the different ways that thecross-channel advertising system 102 can receive information associatedwith consumer 110 interaction with publishers 112 via data channel 114.Returning to FIG. 1, the cross-channel advertising system 102 may alsoreceive information associated with the interaction of consumers 110with businesses 116 via the voice channel 118. To contact businesses116, a consumer typically uses a telephone 128 that is owned orcontrolled by the consumer. For example, the telephone 128 may be theconsumer's home phone, work phone, or mobile phone. In cases where thetelephone 128 is the consumer's mobile phone, the mobile phone and theconsumer's computing system 120 may be one and the same device. Consumercalls are made to a desired business 116 a by dialing the phone numberassociated with that business. The dialed number allows the call to berouted through the public switched telephone network (“PSTN”) or mobilephone network 132 to the business. Consumer calls may be directly routedto the desired business, or terminated at a call center that managescalls for that business. In some embodiments, a business or a callcenter may have an interactive voice response (IVR) system to automatethe interaction with consumers 110 and reduce the required staffinglevels to answer calls.

When a consumer dials a business, the business and/or call center maydetermine the phone number 128 associated with the consumer's phone 130using a caller identification (caller ID) service. With a caller IDservice, the consumer's number is transmitted to the business'stelephone equipment during the ringing signal, or when the call is beingset up but before the call is answered. The detected telephone number iscaptured and stored by the business. A record of the interaction betweenthe business and the consumer may be maintained by the call center orbusiness, and continuously or periodically provided to the cross-channeladvertising system 102. The interaction data may be transmitted to thesystem via an API, delivered via FTP, provided via storage media such asoptical disk, etc.

FIG. 3 is an example of a representative data table 300 containinginteraction data that is provided by a business 116, or by a call centerassociated with a business, to the cross-channel advertising system 102.The data in the table 300 may be used by the system to build a profileof consumers for purposes of identifying re-targeting opportunities.Each row in the table 300 represents an interaction of a consumer with abusiness 116 via the voice channel 118. Each column in the table 300represents a different data field that characterizes the interaction.For example, row 302 of the table corresponds to a call by a consumer toa business to inquire about the address of the business. The first fieldis a reference number field 310 that contains a unique identifier thatis assigned by the business 116 to the interaction record. The referencenumber may be assigned by the business for purposes of internal trackingof the interaction with the consumer. The second field is a user phonenumber field 312 that contains a telephone number (e.g., “608-255-1212”)of the consumer. As noted above, the phone number of the consumer may beautomatically captured by the business or call center using caller ID.Alternatively, the consumer may voluntarily provide their telephonenumber to the business representative that assists them, or providetheir telephone number to an IVR system that handles the call. A timeand date field 314 is populated with a time and date stamp of when theconsumer interaction occurred. In the depicted example, the interactionbetween the consumer and the business or call center occurred at 8:45 amon Jul. 7, 2012.

A transactions field 316 contains a characterization of the consumer'stransaction with the business. In the depicted example, the consumer ischaracterized as having made an inquiry about the address of thebusiness. In contrast, the interaction characterized by row 304 of thetable indicates that the consumer sought a product return. A trackingticket was created by the customer service representative and stored inthe transactions field 316. The interaction characterized by row 306 ofthe table indicates that the consumer purchased an extended warrantyassociated with a product. It will be appreciated that a greater orlesser amount of information characterizing the transaction may beincluded in the transactions field, including a characterization aboutthe particular product or service that was the subject of the inquiryfrom the consumer. In addition, an “other” field 318 may be populated bythe business 116 or call center with any additional information that thebusiness or call center is willing to provide about the consumer'sinteraction.

The data in table 300 is associated with a single business that receivescalls from consumers. As such, the data will typically be associatedwith a single telephone number that is associated with that business. Insome circumstances, a call center may be responsible for receiving callsfor multiple businesses. In such a scenario, the call center may use adialed number identification system (“DNIS”) to determine which one ofthe multiple businesses it provides services for is being called. Suchinformation is captured by the call center and may be added to the dataprovided in table 300. By doing so, the system 102 is able to form anassociation between the user's telephone number and the business that isbeing called.

It will be appreciated that while the information contained in table 300is characterized as being received from a single business, the system102 will typically receive information from multiple businesses. Inthose circumstances, the system may maintain multiple tables 300, eachof which is associated with a corresponding business so that the systemcan track the source of the underlying data. Alternatively, each entryin a table 300 may have an assigned business ID so that the system canassociate each entry in the table with the corresponding business fromwhich it was received.

In some circumstances, tracking phone numbers may be used in thetracking of advertisement performance. In such a scenario, calls fromconsumers to different tracking phone numbers are re-routed to the samebusiness. The tracking number that the consumer dialed may, however, becaptured by the business and added to the data provided in table 300. Bydoing so, the system 102 is able to form an association between theuser's phone number and the tracking number that was called.

It will be appreciated by one skilled in the art that the amount ofinteraction data that is provided by a business to the cross-channeladvertising system 102 may vary from business-to-business. Somebusinesses 116 may be willing to provide significant details associatedwith consumer transactions, as doing so may allow the cross-channeladvertising system 102 to better target advertisements to consumers thatvisit the business. Other businesses may be reticent to share muchinformation with the advertising system 102, so may limit or curtail theamount of data that they provide to the system. In minimalcircumstances, a business may be willing to provide a user phone numberof a consumer and a time and data stamp of the call to facilitatetargeting of advertisements by the advertising system 102.

The foregoing describes the manner in which the cross-channeladvertising system 102 receives information associated with consumer 110interactions with businesses 116 via voice channel 118. Returning toFIG. 1, the cross-channel advertising system 102 uses the informationthat it receives from publishers 112 as well as information that itreceives from businesses 116 to populate the cross-channel targetingdatabase 104. FIG. 4 is an example of a representative data table 400containing identity, impression, and/or activity data that is generatedby the cross-channel advertising system 102 and stored in cross-channeltargeting database 104. The table 400 maintains a correlation between amasked user identifier provided by a publisher and a telephone numberassociated with the consumer. In addition, a confidence level may bestored for each stored tuple (i.e., telephone number, masked useridentifier, publisher). The confidence level reflects the system'sconfidence that the user identifier and the corresponding telephonenumber are associated with the same consumer for the identifiedpublisher.

Each row in the table 400 represents a user telephone number. Thecolumns in the table 400 represent different masked user identifiersthat have been identified as associated with the telephone numbers. Thefirst field is a reference number field 410 that contains a uniqueidentifier that is assigned by the advertising system 102 to the usertelephone number. The reference number may be assigned by theadvertising system for purposes of internal tracking. The first field isa user phone number field 412 that contains a phone number of theconsumer. The phone number may be explicitly or implicitly supplied bythe consumer. The second field is a masked user identifier field 414that is populated with the identifier provided by the publisher. Aspreviously discussed, masked user identifier is mapped by the publisherto a unique user identifier associated with the consumer or theconsumer's device. As previously described, the masked user identifieris typically provided by a publisher or by a manufacturer of a computingdevice. The fourth field is a publisher field 416 that identifies thesource of the masked user identifier. The fifth field is a confidencelevel field 418, reflecting a confidence of the system that the maskeduser identifier and the telephone number are indeed associated with thesame consumer. A confidence level of 100% indicates that the system 102has confirmed that the user identifier and telephone number areassociated with the same consumer. A confidence level above 50%indicates that the system believes that the user identifier andtelephone number are more likely than not associated with the sameconsumer, whereas a confidence level below 50% indicates that the systembelieves that the user identifier and telephone number are likely notassociated with the same consumer. The masked user identifier 414,publisher 416, and confidence level 418 reflect data 420 a received froma single publisher. The system 102 may receive data 420 b . . . 420 nfrom other publishers that are correlated to the same user telephonenumber 412. In such a case, the system 102 stores such data inassociation with the same telephone number so that it might be easilyretrieved.

In some embodiments, publishers 112 or businesses 116 may have providedadditional information to the system 102 that characterizes theconsumer. For example, the publishers or businesses may have providedinformation characterizing advertisements presented to the consumer orpurchases made by the consumer. In such a case, the cross-channeladvertising system 102 may also store such information in table 400. An“other user information” field 422 is contained in the table in theevent that the system 102 stores previous advertisements that werepresented to the consumer or information such as the name, address,email, purchases, etc. of the corresponding consumer. Previousadvertisements or purchases may be used by the system to identify, forexample, those advertisements that are more or less effective on theconsumer.

The cross-channel advertising system populates the table 400 using thedata received from publishers 112 and businesses 116. For example, row402 of the table reflects that the system has 90% confidence that theuser identified by the user identifier “dofBUS” is associated with thephone number “206-555-1212.” Such information and confidence level isderived from row 262 of table 250. In the interaction represented by row262, the consumer provided a phone number to the publisher inconjunction with the purchase of a product. As such, the system mayassume a high confidence that the provided number is accurate. Thesystem may not assume a 100% confidence, however, because the phonenumber may not have been checked as part of the purchase process. As asecond example, row 404 of the table 400 reflects that the system has100% confidence that the user identified by the user identifier“53843DC484” is associated with the phone number “360-555-1234.” Suchinformation and confidence level is derived from row 202 of table 200.The system may assume a 100% confidence that the provided number isaccurate based on knowledge of the publisher that provided the data. Forexample, if the publisher providing the data in table 200 requires auser to establish an account with the publisher, and if the publisherutilizes a verification process where a consumer must establish that theconsumer has possession of a telephone by responding (e.g., by enteringa security code) to a confirmation call made to the telephone, thesystem may assume a 100% confidence in the resulting correlation betweenmasked user ID and user telephone number.

Rows 402 and 404 each represent scenarios where a single publisherprovided the user identifier and the telephone number to thecross-channel advertising system 102. In contrast, row 406 represents ascenario where the system has only received a user identifier associatedwith a consumer from a publisher. As noted in row 260 of table 250, theconsumer associated with the masked user identifier “asgIEB” has nocorresponding phone number provided in user phone number field 214. Insituations where a publisher does not have sufficient information tocorrelate a user identifier with a telephone number, the cross-channeladvertising system 102 may rely on additional information provided frombusinesses 116, for example, in order to determine the correlationitself. One technique for assessing whether a user identifier might beassociated with a telephone number is for the system to look forsituations where a tracking phone number is displayed to a consumer inan advertisement at time A, and a call is received to that trackingphone number at time B, where time B is in close proximity to time A. Ifthe call is received in sufficiently close time proximity, the system102 may imply that the displayed advertisement caused the call to thetracking number, and that the user identifier associated with theadvertisement therefore is the same consumer that placed the call. As anexample, in table 250 it is noted that user “asgIEB” was displayed anadvertisement containing a tracking number “{TRACKING #}” at Jul. 7,2012, at 8:42 am. If, for sake of the example, the table 300 representedcalls that are made to tracking number “{TRACKING #}”, the system maysearch table 300 for calls that were received soon after 8:42 am on July7th. As shown in row 302, a call is noted as having been received from anumber “608-555-1212” at 8:45 am on July 7th. Because the call wasreceived only 3 minutes after the advertisement was displayed, thesystem may assume that the consumer placing the call was the same as theconsumer that viewed the advertisement. As such, in row 406 the systemrecords a correlation between user identifier “asgIEB” and the telephonenumber “608-555-1212.” Since the system cannot be certain that theconsumer viewing the advertisement is the same as the consumer makingthe call, the system assigns a confidence level of 70% to the useridentifier/telephone number pair. It will be appreciated that variousmethodologies may be used to derive the confidence level in suchcircumstances. For example, the closer in time between the advertisementand the receipt of the call, the higher the confidence level. Thefarther in time between the advertisement and the receipt of the call,the lower the confidence level.

Different models to determine confidence levels can be set by the systemfor each publisher. For those publishers that merely provide minimalinformation to the system, such as only the masked user identifier andphone number, the system may apply a default confidence level. Thedefault confidence level may be based on, for example, the knownpractices of the publisher, the historical reliability of the publisher,or the general reliability of the class of publishers to which thepublisher belongs. Publishers that publish advertisements more broadlyacross multiple websites or applications may have a lower confidencelevel, whereas publishers that publish in a more limited fashion (e.g.,on a single website) may have a higher confidence level. As anotherexample, the system may assign a higher confidence level if a publisherprovides data that links the same masked user identifier to the samephone number multiple times (e.g., as a result of several interactionswith a consumer). In contrast, the system may assign a lower confidencelevel if a publisher provides only a single instance that links a maskeduser identifier to a phone number.

While FIGS. 2-4 depict tables whose contents and organization aredesigned to make them more comprehensible by a human reader, thoseskilled in the art will appreciate that the actual data structure(s)used by the facility to store this information may differ from thetables shown, in that they, for example, may be organized in a differentmanner, may contain more or less information than shown, may becompressed and/or encrypted, and may be optimized in a variety of ways.

Once the cross-channel targeting database 104 has been built by thecross-channel advertising system 102, businesses and publishers may takeadvantage of the link between telephone numbers and user identifiers inorder to better target consumers with advertisements. FIG. 5 is a flowdiagram illustrating a process 500 implemented by the cross-channeladvertising system 102 for performing cross-channel targeting ofadvertisements. The process 500 is performed in part or in full by thecross-channel advertising system 102. Some or all steps may be executedby the processor 120, and stored as computer executable instructions inthe memory 122.

At a block 502, a business 116 receives a call from a consumer 110. Forexample, a consumer 110 a may utilize phone 130 to dial the businessnumber “1-800-NORTHCO.” As was previously described, a call center mayutilize automatic number identification or caller ID to determine theconsumer phone number 128. The call center can also determine the dialednumber (e.g., “1-800-NORTHCO”). The business 116 a may store informationsuch as an ANI-determined consumer phone number (“206-555-0001”), thetime of the call, the number dialed, and so on, in table 300.

At a block 504, the business 116 determines that the consumer phone callterminated early. For example, the consumer 110 a may have started abusiness transaction with the NorthCo call center, but the call may havebeen dropped or the consumer may have decided to not complete thetransaction. An operator at the call center may enter an indication ofthe failure to complete the phone transaction that gets stored in thetable 300, or the IVR system may store a current IVR state at the timeof the call drop in the table 300. Although not shown in table 300,additional details may be stored, such as at what point in an IVRsession (e.g., during which menu and state) the call terminated. Forexample, while using an IVR system the consumer may have reached a menuoption requesting the consumer to enter credit card information. If theconsumer did not have a credit card readily available, the consumer mayhave hung up the phone. In such circumstances, it may be especiallyadvantageous for NorthCo to “re-target” the consumer in order to try toget the consumer to re-perform the transaction to completion.

At block 505, the business 116 sends a re-targeting request to thecross-channel advertising system 102. The re-targeting request includesthe phone number of the consumer that is to be re-targeted. There-targeting request may also include an indication of a particularadvertising treatment or advertising campaign that is to be displayed tothe targeted consumer. Depending on the relationship between thebusiness and the cross-channel advertising system, the request may alsoinclude an amount that the business is willing to pay for the targetedadvertisement. The amount paid for the advertisement may be on aper-impression basis, on a per-click basis, on a per-call basis, orbased on some other agreed financial arrangement as is common in theonline advertising industry. The business then continues to receivecalls from additional consumers at block 502. Although FIG. 5 depicts atargeting request being made immediately after a terminated consumerinteraction, it will be appreciated that the targeting request may bemade periodically (e.g., hourly, daily, weekly) and encompass anaggregate number of consumers that the business is interested intargeting based on interactions with the consumer during the precedingperiod.

At block 506, the cross-channel advertising system 102 receives therequest to re-target a consumer. As noted, the request includes theconsumer phone number and an indication of a desired advertisement. Therequest may also include other information that the business would liketo provide to facilitate the targeted advertising. For example, therequest may include a desired time of day, cap on number of times anadvertisement should be presented to a consumer, or desired price togenerate the call from the consumer. In addition, the request mayinclude a preference about the publisher or type of publisher with whichthe business is willing to advertise. Businesses may have strongpreferences for certain types of publishers over others. Some publishersmay have desirable brands with which the business would like to beassociated. Other publishers may have weaker brands or content that abusiness would like to avoid. Using a blacklist or a whitelist, abusiness may therefore specify which publishers the business would liketo avoid and/or which publishers the business would like to target. Thepublisher may be identified by name (e.g., a request to publish with the“New York Times”), the publisher may be identified by type (e.g., arequest not to publish with any alcohol beverage manufacturers), or thepublisher may be identified by other keyword or criteria limitation. Ifnot specified by a business, the system may select publishers that arelikely to provide the highest likelihood of success for the desiredadvertisements.

At a block 508, the system uses the received telephone number as anindex to the cross-channel targeting database 104 to retrieve the maskeduser identifier corresponding to the telephone number from the database.For example, the system may use the number “608-555-1212” to retrievethe corresponding masked user identifier “asglEB” as shown in row 406 oftable 400. The system also retrieves the publisher associated with themasked user identifier 414, as well as a confidence level of theassociated user identifier. In the example, the retrieved publisher is“Google” and the confidence level is “70%.” In the event that more thanone masked user identifier is associated with the received telephonenumber, the system retrieves all masked user identifiers and associatedpublishers.

At a block 510, the system selects a first masked user identifier toanalyze. At a decision block 512, the system determines whether theselected masked user identifier is associated with a desired publisher.As previously noted, businesses may desire that advertisements only beplaced with certain publishers. If the publisher corresponding to theselected first masked user identifier is not a desired publisher,processing continues to a decision block 514 where the system determineswhether any additional masked user identifiers remain to be analyzed. Ifno masked user identifiers remain to be analyzed, processing halts.Otherwise, processing returns to block 510 where the next masked useridentifier is selected and the processing of blocks 512 repeats.

If the system determines that the selected masked user identifier isassociated with a desired publisher at decision block 512, processingcontinues to a decision block 516. At decision block 516, the systemcompares the retrieved confidence level to a threshold desiredconfidence level. The desired confidence level may be configured by asystem operator, may be determined by the business requesting thetargeted advertisement, or may determined algorithmically to meet returnon investment (ROI) goals of the advertising campaigns. For example, abusiness may specify that they do not want to target a consumer if theconfidence that the user identifier is associated with the telephonenumber does not exceed 75%. If the confidence level does not exceed thedesired threshold level at decision block 516, processing proceeds toblock 518 where the advertising message is not targeted to the useridentifier. If, however, the confidence level exceeds the thresholdlevel at decision block 516, processing proceeds to a block 520.

At block 520, the system 102 causes a re-targeting message to betransmitted to the consumer via data channel 114 and the selectedpublisher 116. For example, the system may request that thecorresponding publisher display a desired targeted advertisement oradvertising campaign to the consumer the next time the consumer uses aweb browser 136 to access a website of the publisher. The publisheridentifies the consumer by the masked user identifier that is providedby the system 102. The publisher retrieves the unique user identifierthat corresponds to the masked user identifier, and uses the unique useridentifier to serve advertisements to the desired consumer. A publisher116 may notify the system 102 when the requested advertising has beendelivered to the desired consumer. If the requested advertising is notdelivered to the desired consumer within a specified timeframe, therequest by the system to have the advertisement be displayed by thepublisher may lapse.

The delivered re-targeting message should ideally be tailored toencourage the consumer to complete the previously terminated engagement,or to otherwise reengage with the business. For example, the deliveredadvertising message may allow a consumer to bypass unnecessary menusthat would otherwise make completing or reinitiating the transactionmore cumbersome. For example, the consumer may be presented a specialphone number for directly reaching a call center agent (e.g., bypassingthe IVR) who can directly request the credit card information tocomplete the terminated transaction.

In some embodiments, the re-targeting message is further tailored basedon other known information about the consumer. For example, theadvertisement may be tailored based on past advertisements alreadydisplayed to the consumer, past purchases of the consumer, known likesor dislikes of a consumer, demographic information characterizing theconsumer, etc.

In some embodiments, a business may be charged for an advertisementbased on the confidence level associated with the targeted consumer.Advertisements that are targeted at user identifiers having a higherconfidence level are charged more, and advertisements that are targetedat user identifiers having a lower confidence level are charged less.The differential charging is intended to compensate for the reduction inaccuracy associated with targeting user identifiers having a lowerconfidence level.

In some embodiments, a publisher 112 will provide a masked useridentifier to the cross-channel advertising system 102 and solicitadvertisements to present to the masked user identifier. In such ascenario, the cross-channel advertising system 102 can determine whetherany outstanding advertising requests remain to be targeted to theidentified consumer and publisher. If advertising requests remainoutstanding, the system responds to the publisher 112 with the desiredadvertising treatment for the consumer. In this fashion, the system mayrespond in an on-demand fashion in order to target consumers at the timethat they visit a publisher website or application.

While the previously-provided example of re-targeting pertained to aconsumer that had an interrupted transaction with a business, it will beappreciated that a business may opt to re-target consumers for a varietyof reasons. For example, a business may desire to re-target a group ofconsumers that have recently purchased a particular product in the hopeto upsell the consumers with warranty or extended service contracts,complementary products (e.g., cases, accessories, etc.), or othervalue-added product or service. As another example, businesses may wishto re-target consumers that they have recently lost. By offering adiscount or other benefit to a consumer, the business may successfullyconvince the consumer to give the business a second chance. It will beappreciated that the disclosed technology allows businesses to targetconsumers for a variety of different reasons in a manner that is notvery intrusive to the consumer.

In some embodiments, a business 116 may use the cross-channeladvertising system 102 to target existing or new consumers, regardlessof any prior interaction that the business may have had with theconsumers. For example, a business may have generated a list ofconsumers and corresponding telephone numbers of the consumers that theyare trying to reach. The list may be constructed, using third-partydatabases which allow consumers to be identified and selected based onvarious consumer characteristics (e.g., geography, demographics). Thebusiness can provide a list of consumer telephone numbers to the system,which can then target advertisements to those consumers using themethodology described herein. A business can measure the effectivenessof digital advertising (e.g., brand advertising) using the system 102 bydetermining whether advertising campaigns distributed in such a fashiongenerated incrementally more phone calls from consumers than consumerswho were called or targeted through other traditional forms of media(e.g., print media).

On a periodic or continuous basis, the system 102 may audit thecross-channel targeting database 104 and remove or modify entries in thedatabase to maintain the currency of the database. Entries in thedatabase may be removed or modified based on a variety of factors. Forexample, the system 102 may remove any telephone numbers that haven'tbeen targeted within a certain period (e.g., 1 year, 18 months). Asanother example, the system 102 may remove those masked user identifiersthat are associated with publishers that have a tendency to underperformas compared to an average of all publishers or of like publishers. Acontinued underperformance of advertisements associated with aparticular masked user identifier suggests that the confidence levelbetween the masked user identifier and telephone number is likely wrong.For example, an individual may have borrowed a friend's phone to visit awebsite, and the identification of the individual by the publisher ofthe website has therefore proven to be an incorrect correlation with thetelephone number of the phone. Rather than immediately delete a maskeduser identifier from the database, the system may instead decrease theconfidence level to reflect the reduction in confidence that thetelephone number is indeed associated with the consumer. Masked useridentifiers having a confidence factor that falls below a certainthreshold (e.g., 25%) may be automatically removed from the database.

Alternate Embodiments

In some embodiments, a customer relationship management (CRM) softwaresystem may assist the cross-channel advertising system 102 inassociating additional user information with the information in thecross-channel targeting database 104. For example, a consumer'spassword, Social Security number, business account information, and soon may be beneficially linked, joined by, or augmented with theadditional information in the cross-channel targeting database 104.

In some embodiments, the cross-channel advertising system 102 mayreceive information from publishers or businesses that allow multiplephone numbers to be associated with a unique user identifier. Forexample, a user may have a mobile phone, a work phone, and a home phone.In this case, the system 102 merely associates each phone number withthe same user identifier. In this fashion, a business is able to targeta consumer by providing any phone number associated with the consumer tothe system.

In some embodiments, a consumer making a voice-over-Internet protocol(VoIP) phone call may expose a phone number in a session initiationprotocol (“SIP”) message setting up the session. The cross-channeladvertising system 102 may use the header information to associate theconsumer's phone number with a user identifier.

In some aspects, the system 102 will store information regarding how theuser responds to a re-targeting message in order to track how effectivere-targeting is for either that person individually, or collectively howeffective the campaign is overall. This information may be used torefine parameters of the re-targeting campaign to improve itseffectiveness.

Those skilled in the art will appreciate that the depicted flow chartsmay be altered in a variety of ways. For example, the order of the stepsmay be rearranged, steps may be performed in parallel, steps may beomitted, or other steps may be included. Those skilled in the art willfurther appreciate that the actual implementation of the database maytake a variety of forms, and the term “database” is used herein in thegeneric sense to refer to any area that allows data to be stored in astructured and accessible fashion using such applications or constructsas databases, tables, linked lists, flat files, arrays, and so on.

It will be appreciated that the system 102 (and environment 100) includemultiple elements coupled to one another and each element is illustratedas being individual and distinct. However in some embodiments some orall of the components and functions represented by each of the elementscan be combined in any convenient and/or known manner or divided overmultiple components and/or processing units. Furthermore the functionsrepresented by the components can be implemented individually or in anycombination thereof, in hardware, software, or a combination of hardwareand software. Different and additional hardware modules and/or softwareagents may therefore be included in the environment 100 and/or system102 without deviating from the scope of the disclosure.

We claim:
 1. A method in a computing system for generating a dataset ofcorrelations between user identifiers and telephone numbers, the methodcomprising: receiving, at a computing system, impression datacharacterizing exposures of users to a mechanism for contactingbusinesses, the impression data comprising, for each incidence ofexposure to the mechanism, a user identifier used to track that a userwas exposed, a phone number associated with the exposure, and a date andtime associated with the exposure; receiving, at the computing system,call data describing telephone calls made to businesses, the call datacomprising, for each call, a caller telephone number, a callee telephonenumber, and a date and time that the call was placed from the caller tothe callee; determining, by the computing system, a correlation betweena caller telephone number from the call data and a user identifier fromthe impression data by: identifying a callee telephone number from thecall data; identifying, from the impression data, an exposure with anassociated phone number that is the same as the callee telephone number;identifying, from the call data, a telephone call associated with thecallee telephone number; comparing the date and time associated with theidentified exposure to the date and time associated with the identifiedtelephone call; forming a correlation between the user identifier of theidentified exposure and the caller telephone number of the identifiedtelephone call based on the comparison; and assigning a confidence levelto the determined correlation based on the compared date and time; andstoring, in a correlation dataset, a correlation entry comprising thecaller telephone number, the user identifier, and the confidence level.2. The method of claim 1, wherein the exposure to the mechanism forcontacting businesses occurs on websites or applications.
 3. The methodof claim 1, wherein the exposure to the mechanism for contactingbusinesses occurs in advertisements.
 4. The method of claim 1, wherein auser identifier is associated with a computing device used by a consumerto access a publisher website or application over a data channel.
 5. Themethod of claim 4, wherein the user identifier is a cookie or anInternational Mobile Station Equipment Identity (IMEI).
 6. The method ofclaim 1, wherein the confidence level reflects a likelihood that a userassociated with the user identifier is the same user as is associatedwith the caller telephone number.
 7. The method of claim 1, whereincomparing the date and time associated with the identified exposure tothe date and time associated with the identified telephone callcomprises: evaluating instances in which the date and time of thecorresponding call are after and proximate to the date and time of theidentified exposure.
 8. The method of claim 7, wherein the time of thecorresponding call is within three minutes of the time of the identifiedexposure.
 9. The method of claim 1, further comprising: receiving arequest from a business to re-target a consumer associated with a callertelephone number; retrieving from the correlation dataset a correlationentry associated with the caller telephone number, the correlation entrycomprising a user identifier and confidence level; determining whetherthe confidence level satisfies a confidence threshold; and based on thedetermination, transmitting a request to a publisher associated with theuser identifier to cause an advertisement to be presented to a userassociated with the user identifier via a publisher website orapplication.
 10. A non-transitory computer-readable medium encoded withinstructions that, when executed by a processor, perform a method forgenerating a dataset of correlations between user identifiers andtelephone numbers, the method comprising: receiving, at a computingsystem, impression data characterizing exposures of users to a means forcontacting businesses, the impression data comprising, for eachincidence of exposure to the means, a user identifier used to track thata user was exposed, a phone number associated with the exposure, and adate and time associated with the exposure; receiving, at the computingsystem, call data describing telephone calls made to businesses, thecall data comprising, for each call, a caller telephone number, a calleetelephone number, and a date and time that the call was placed from thecaller to the callee; determining, by the computing system, acorrelation between a caller telephone number from the call data and auser identifier from the impression data by: identifying a calleetelephone number from the call data; identifying, from the impressiondata, an exposure associated with a phone number that is the same as thecallee telephone number; identifying, from the call data, a telephonecall associated with the callee telephone number; comparing the date andtime associated with the identified exposure to the date and timeassociated with the identified telephone call; forming a correlationbetween the user identifier of the identified exposure and the callertelephone number of the identified telephone call based on thecomparison; and assigning a confidence level to the determinedcorrelation based on the compared date and time; and storing, in acorrelation dataset, a correlation entry comprising the caller telephonenumber, the user identifier, and the confidence level.
 11. Thenon-transitory computer-readable medium of claim 10, wherein theexposure to the means for contacting businesses occurs on websites orapplications.
 12. The non-transitory computer-readable medium of claim10, wherein the exposure to the means for contacting businesses occursin advertisements.
 13. The non-transitory computer-readable medium ofclaim 10, wherein a user identifier is associated with a computingdevice used by a consumer to access a publisher website or applicationover a data channel.
 14. The non-transitory computer-readable medium ofclaim 13, wherein the user identifier is a cookie or an InternationalMobile Station Equipment Identity (IMEI).
 15. The non-transitorycomputer-readable medium of claim 10, wherein the confidence levelreflects a likelihood that a user associated with the user identifier isthe same user as is associated with the caller telephone number.
 16. Thenon-transitory computer readable medium of claim 10, wherein comparingthe date and time associated with the identified exposure to the dateand time associated with the identified telephone call comprises:evaluating instances in which the date and time of the correspondingcall are after and proximate to the date and time of the identifiedexposure.
 17. The non-transitory computer-readable medium of claim 16,wherein the time of the corresponding call is within three minutes ofthe time of the identified exposure.
 18. The non-transitorycomputer-readable medium of claim 10, further encoded with instructionsthat when executed by the processor perform the method for generating adataset of correlations between user identifiers and telephone numbers,the method further comprising: receiving a request from a business tore-target a consumer associated with a caller telephone number;retrieving from the correlation dataset a correlation entry associatedwith the caller telephone number, the correlation entry comprising auser identifier and confidence level; determining whether the confidencelevel satisfies a confidence threshold; and based on the determination,transmitting a request to a publisher associated with the useridentifier to cause an advertisement to be presented to a userassociated with the user identifier via a publisher website orapplication.